The ultimate goal of the HIVE MC-IU effort is to develop a common coordinate framework (CCF) for the healthy human body that supports the cataloguing, exploration, and download of different types of tissue and individual cell data. The CCF will use different visual interfaces in order to exploit human and machine intelligence to improve data exploration and communication. The proposed effort combines decades of expertise in data and network visualization, scientific visualization, biology, and biomedical data standards. The goal is to develop a highly accurate and extensible multidimensional spatial basemap of the human body with associated data overlays. This basemap will be designed for online exploration as an atlas of tissue maps composed of diverse cell types, developed in close collaboration with the HIVE MC-NYGC team. To implement this functionality, we will develop methods to map and connect metadata, pixel/voxel data, and extracted vector data, allowing users to ?navigate? across multiple levels (whole body, organ, tissue, cells). MC-IU will work in close collaboration with the HIVE Infrastructure and Engagement Component (IEC) and tools components (TCs) to connect and integrate further computational, analytical, visualization, and biometric resources driven by spatial context.
This project will create a high-resolution, functional mapping of voxel, vector, and meta datasets in support of integration, interoperability, and visualization of biomedical HuBMAP data and models. We will create an extensible common coordinate framework (CCF) to facilitate the integration of diverse image-based data at spatial scales ranging from the molecular to the anatomical. This project will work in close coordination with the HuBMAP consortium to help drive an ecosystem of useful resources for understanding and leveraging high-resolution human image data and to compile a human body atlas.
